S.E.D is supported by start-up funds provided by the Department of Molecular&#160;Medicine, The University of South Florida, as well as a CFF research grant (DARCH19G0) the N.I.H (5R21AI147654 - 02 (PI, Chen)) and the USF Institute on Microbiomes. We thank the Whiteley lab for ongoing collaboration involving data sets related to this manuscript. We thank Dr. Charles Szekeres for facilitating FACS sorting. Figures were created by A.D.G and S.E.D using Biorender.com.

1. Prepare synthetic cystic fibrosis medium (SCFM2)
NOTE: Preparation of SCFM2 comprises three main stages outlined below (Figure 2). For full details and references, see9,10,12.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/62420/62420fig02.jpg" /> 
Figure 2:&#160;Preparation and inoculation of SCFM2 medium. (A) Buffered base is prepared using salts and amino acids listed in Table 1 and Table 2. Buffered base can be stored at 4 &#176;C for up to 30 days, but must be protected from light exposure. (B) Mucin and DNA are added to an aliquot of buffered base and dissolved into solution overnight at 4 &#176;C. (C) Lipid and additional stocks are added to the overnight solution and incubated at 37 &#176;C with agitation at 250 rpm for 20 min. SFCM2 is then inoculated with washed, log phase cells at an OD600 = 0.05. Abbreviations: SCFM2 = synthetic cystic fibrosis sputum medium. <a href="https://www.jove.com/files/ftp_upload/62420/62420fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol>
	<li>Sterilization of porcine mucin
	<ol>
		<li>Prepare sterile mucin at a final concentration of 5 mg/mL in SCFM2. For example, for a 5 mL volume of SCFM2, weigh 25 mg of Type II mucin in a sterile Petri dish, and place into an ultraviolet (UV) sterilizer for 4 h, gently agitating every hour.</li>
		<li>After 4 h, transfer the UV-treated mucin into autoclaved 1.7 mL tubes under sterile conditions, and store at -20 &#176;C.</li>
		<li>To confirm complete sterilization, dissolve a sample of mucin in a sterile liquid, such as water or Luria Bertani (LB) broth, and observe under a microscope. 
		NOTE: Sterilized mucin can be stored at -20 &#176;C for up to 6 months.</li>
	</ol>
	</li>
	<li>Preparation of buffered base
	<ol>
		<li>Prepare salt and amino acid stock solutions by adding the appropriate amounts by weight to deionized water as listed in Table 1. Filter-sterilize all stock solutions using a 0.22 &#956;m filter, wrap in foil to protect from light degradation, and store at 4 &#176;C for up to one month.</li>
		<li>Prepare buffered base by combining 190 mL of deionized water with amino acid and salt stock solutions by volumes listed in Table 1. Adjust the solution to pH 6.8, and increase to a final volume of 250 mL. Filter-sterilize using a 0.22 &#956;m filter, and store at 4 &#176;C for up to 30 days.</li>
		<li>On the evening before the experiment, aliquot the desired amount of buffered base into a glass culture flask, and add mucin (5 mg/mL as described in step 1.1.1) and purified salmon sperm DNA (0.6 mg/mL).&#160;Agitate gently, wrap in foil, and leave at 4 &#176;C overnight to allow mucin and DNA to dissolve into solution. 
		NOTE: Salmon sperm DNA aliquots should be thawed on ice, vortexed, and added to buffered base and mucin. Tryptophan, asparagine, and tyrosine stock solutions must be prepared in solutions of NaOH (see Table 1 for concentrations) instead of deionized water. Keep buffered base and all stock solutions wrapped in foil to protect from light exposure. Most stocks will be stable for up to a month. Stocks that become discolored should not be used and should be replaced before use.</li>
	</ol>
	</li>
	<li>Addition of supplemental stocks
	<ol>
		<li>On the day of the experiment, add the stocks listed in Table 2 to the buffered base containing mucin and DNA. 
		NOTE: Prepare a fresh FeSO4 solution on the day of the experiment, but all other stocks can be made ahead of time and stored for 30 days at 4 &#176;C. 1,2-Dioleoyl-sn-glycero-3-phosphocholine (DOPC) contains chloroform. Handle with caution, and do not use near open flames. After the addition of DOPC, incubate SCFM2 at 37 &#176;C with shaking (250 rpm) for at least 20 min (for 5 mL culture). This incubation period allows the chloroform in the DOPC to evaporate. The flask should not be airtight; instead, cover the flask opening loosely with foil.</li>
	</ol>
	</li>
</ol>
2. Real time assessment of antimicrobial tolerance in bacterial aggregates
<ol>
	<li>Prepare overnight cultures
	<ol>
		<li>On the evening before the experiment, inoculate 5 mL of LB broth with several colonies of Pa PAO1-pMRP9-113 from an LB agar plate containing antibiotic (carbenicillin 300 &#956;g/mL). Grow overnight at 37 &#176;C with agitation at 250 rpm. 
		NOTE: Grow overnight cultures with the addition of antibiotics required for the selection of required plasmids (here, the green fluorescent protein (GFP) expression plasmid, pMRP9-1). Note that Pa cells are to be washed before SCFM2 is inoculated. LB may be substituted for other rich laboratory media for overnight cultures. All bacterial isolates should be handled using appropriate BSL-2 guidelines throughout this protocol.</li>
	</ol>
	</li>
	<li>Inoculate SCFM2
	<ol>
		<li>On the day of the experiment, back-dilute overnight cultures of Pa 1:10 (culture: liquid media) by inoculating 500 &#956;L into 5 mL of fresh LB broth. Grow cells until log phase (60-90 min) at 37 &#176;C with agitation at 250 rpm.</li>
		<li>Centrifuge log phase cultures at 10,000 &#215; g for 5 min. Wash the cells by removing the supernatant and resuspending in 3 mL of filter-sterilized phosphate-buffered saline (PBS, pH 7.0). Repeat twice, and resuspend the pellet in a final volume of 1 mL of PBS.</li>
		<li>Measure the absorbance of the washed cells using a spectrophotometer at 600 nm (OD600), and calculate the volume of culture required for a starting OD600 of 0.05 in 5 mL of SCFM2. Inoculate Pa into the SCFM2, and vortex gently to distribute cells throughout. Pipette 1 mL of the inoculated SCFM2 into each chamber of a 4-well, glass bottom, optical dish, and incubate for 4 h statically at 37 &#176;C. 
		NOTE: The doubling time of Pa cultures is dependent on the strain and the availability of oxygen. In SCFM2, under the conditions described here, the doubling time of Pa is ~1.4 h10.</li>
	</ol>
	</li>
</ol>
3. Visualizing aggregates during antibiotic treatment with confocal laser scanning microscopy (CLSM)
NOTE: This section describes the use of confocal laser scanning microscope and image capture software for the imaging of Pa aggregates in SCFM2. The goal is to observe and characterize the remaining (tolerant) bacterial biomass after treatment with antibiotics. The steps outlined can be performed with success on other confocal microscopes, although the instrument operating manual should be referenced for specific guidance.
<ol>
	<li>Image Pa cultures using either a heated chamber or a heated microplate fitted on the microscope stage to maintain an ambient temperature of 37 &#176;C. Start the Incubation module at least 2 h prior to the beginning of the experiment to allow all apparatus to reach the desired temperature, and reduce further expansion and movement during data collection.</li>
	<li>After 4 h, transfer SCFM2 cultures containing Pa cells to the heated microscope stage. Designate 3 out of 4 wells as technical replicates for antibiotic treatment, and consider the 4th well as a no-treatment control, containing only Pa cells in SCFM2, without antibiotic. Identify aggregates using brightfield microscopy within the Locate tab prior to any excitation of fluorescent reporters. Define an area for imaging within each well, and store its position (x-y-z coordinates) using the Positions module in the imaging software.</li>
	<li>Use a 63x oil-immersion objective to visualize Pa cultures containing the GFP expression plasmid pMRP9-1 in SCFM2 with an excitation wavelength of 488 nm and emission wavelength of 509 nm. Take images using the z-stack option within the Acquisition module at 1 &#956;m intervals (total of 60 slices). Use the Line-averaging module to reduce background fluorescence in the GFP channel within the total volume of the 60 &#956;m z-stack images (1,093.5 mm3). Take control images of uninoculated SCFM2 by using identical settings to determine the background fluorescence for image analysis. 
	NOTE: Images are acquired by producing 512 pixels x 512 pixels (0.26 &#956;m x 0.26 &#956;m pixels) 8-bit z-stack images that are 60 &#956;m from the base of the coverslip.</li>
	<li>Use the time series option within the imaging software to capture 60 slices at each position (well) at 15-min intervals over a period of 18 h. Use the definite focus strategy within the software to store a focal plane for each position, which is returned to at each time point throughout the experiment.</li>
	<li>After a total 4.5 h of incubation, image each position using the above settings to determine the aggregate biomass within each of the four wells before the addition of antibiotic.</li>
	<li>After 6 h of total incubation, add antibiotic at 2x-below minimum inhibitory concentration (MIC) to each replicate. Pipette directly and gently into the middle of the well, just below the air-liquid interphase. Maintain all cultures in the heated confocal chamber. 
	NOTE: Here, colistin sulfate at a concentration of 140 &#956;g/mL was used.</li>
	<li>Begin imaging post-antibiotic treatment by clicking on the Start Experiment option within the imaging program. 
	&#8203;NOTE: Antibiotic concentration used is dependent on the antibiotic, the Pa isolate, and whether the user would like to examine killing or tolerance effects. This experiment uses a single dose. Additional doses can be added without disrupting cultures if needed.</li>
</ol>
4. Propidium iodide staining of Pa aggregates
NOTE: Propidium iodide (PI) is commonly utilized as a staining reagent to identify non-viable (dead) bacterial cells in culture. Here, it is used to identify aggregates sensitive to antibiotic treatment applied in section 3. Throughout this protocol, the expression and detection of GFP in Pa cells is used as the main proxy for cell viability. This final step allows confocal imaging to be used once more to identify the spatial positioning of live/dead aggregates in relation to each other. Additionally, aggregates are identified as live/dead for further downstream cell sorting in section 5.
<ol>
	<li>After 18 h, add PI to each well of the four-chambered optical bottom dish containing SCFM2 cultures. Follow the manufacturer&#39;s instructions for the volume of PI and incubation time (e.g., ~2 &#956;L per mL of culture, ~20-30 min).</li>
</ol>
5. Isolating live cells from aggregates using a FACS approach
NOTE: FACS presents a powerful platform to sort and isolate groups of cells according to a fluorescently tagged phenotype. Here, FACS is used to isolate live (antibiotic tolerant) aggregates from non-viable aggregates.
<ol>
	<li>After staining with propidium iodide, remove the cultures from incubation, and transfer to a FACS instrument in an insulated container to maintain 37 &#176;C.</li>
	<li>Run 1 mL aliquots of SCFM2 containing Pa aggregates at the lowest flow rate. 
	NOTE: Each aliquot will contain ~15,000 aggregates.</li>
	<li>To detect GFP, illuminate the cells with a 488 nm laser, and record the fluorescent signal height at 530/30 nm. Visualize the PI staining by excitation with a 561 nm laser, and record the fluorescent signal height at 610/20 nm. Perform sorting using a 70-u nozzle. 
	&#8203;NOTE: Sorted aggregates can be pooled in multiple ways depending on the user&#39;s application. In this case, FACS was used to sort viable Pa aggregates for downstream RNA sequencing. Alternative applications are discussed below.</li>
</ol>
6. Image analysis
NOTE: Time-lapse microscopy generates large amounts of data. An 18-h experiment for the observation of Pa aggregates in SCFM2 identifies ~50,000 aggregates over time, which have the potential to be characterized for volume and spatial positioning. Use an image analysis software to quantify aggregate dynamics in SCFM2:
<ol>
	<li>For aggregate studies in SCFM2, quantify the background GFP fluorescence by creating a histogram of counts in the GFP channel that is produced for uninoculated SCFM2 and SCFM2 inoculated with Pa strain PAO1 carrying pMRP9-1. To ensure that detected GFP voxels correlate to Pa biomass, define a GFP+ voxel as &#8805;1.5x the GFP background count value. 
	NOTE: The background fluorescence is defined as the highest voxel value of three randomly chosen positions, averaged. Background counts are, as a standard measure, subtracted from all pixels in experimental images by the image analysis software.</li>
	<li>After background subtraction in the Surpass module, produce isosurfaces for all remaining voxels.</li>
	<li>To detect individual aggregates, enable the Split Objects option, and define aggregates as objects with volumes of &#8805;5 &#956;m3. Use the Vantage module in the image analysis software to calculate the volume, x-y-z, and sum of GFP voxels for each individual object. Export this data to an external statistical platform. 
	NOTE: Some image analysis software permit the export of multiple quantitative phentoypes at once, allowing for correlations to be calculated.</li>
	<li>Filter data exported from the Vantage module by size to ensure that no objects of &#60;0.5 &#181;m3 (dispersed biomass) remain. For each individual object within the image, calculate the distance from itself in relation to other objects (aggregates) using the Vantage module of the image analysis software or manually with the following equation. 
	d = sqrt((x2&#8722; x1)2 + (y2&#8722; y1)2 + (z2&#8722; z1)2) (1)</li>
	<li>Use SUM and AVERAGE calculations to find the total biomass and average aggregate volume. Alternatively, export data into other statistical platforms or scripts, e.g., the distribution of aggregates across biomass as discussed in the representative results (script unpublished in collaboration with the Whiteley laboratory, Georgia Institute of Technology).</li>
</ol>

<ol>
	<li>Ramsay, K. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+changing+prevalence+of+pulmonary+infection+in+with+fibrosis:+A+longitudinal+analysis.">The changing prevalence of pulmonary infection in with fibrosis: A longitudinal analysis.</a> Journal of Cystic Fibrosis. 16 (1), 70-77 (2017).</li><li>Bessonova, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data+from+the+US+and+UK+cystic+fibrosis+registries+support+disease+modification+by+CFTR+modulation+with+ivacaftor.">Data from the US and UK cystic fibrosis registries support disease modification by CFTR modulation with ivacaftor.</a> Thorax. 73 (8), 731-740 (2018).</li><li>Breuer, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Changing+prevalence+of+lower+airway+infections+in+young+children+with+cystic+fibrosis.">Changing prevalence of lower airway infections in young children with cystic fibrosis.</a> American Journal of Respiratory and Critical Care Medicine. 200 (5), 590-599 (2019).</li><li>O'Donnell, J. N., Bidell, M. R., Lodise, T. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Approach+to+the+treatment+of+patients+with+serious+multidrug-resistant+Pseudomonas+aeruginosa+infections.">Approach to the treatment of patients with serious multidrug-resistant Pseudomonas aeruginosa infections.</a> Pharmacotherapy. 40 (9), 952-969 (2020).</li><li>Bjarnsholt, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+in+vivo+biofilm.">The in vivo biofilm.</a> Trends in Microbiology. 21 (9), 466-474 (2013).</li><li>Darch, S. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+determinants+of+quorum+signaling+in+a+Pseudomonas+aeruginosa+infection+model.">Spatial determinants of quorum signaling in a Pseudomonas aeruginosa infection model.</a> Proceedings of the National Academy of Sciences of the United States of America. 115 (18), 4779-4784 (2018).</li><li>Zhu, K., Chen, S., Sysoeva, T. A., You, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Universal+antibiotic+tolerance+arising+from+antibiotic-triggered+accumulation+of+pyocyanin+in+Pseudomonas+aeruginosa.">Universal antibiotic tolerance arising from antibiotic-triggered accumulation of pyocyanin in Pseudomonas aeruginosa.</a> PLoS Biology. 17 (12), 3000573 (2019).</li><li>Ciofu, O., Tolker-Nielsen, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tolerance+and+resistance+of+Pseudomonas+aeruginosa+biofilms+to+antimicrobial+agents-how+P.+aeruginosa+can+escape+antibiotics.">Tolerance and resistance of Pseudomonas aeruginosa biofilms to antimicrobial agents-how P. aeruginosa can escape antibiotics.</a> Frontiers in Microbiology. 10, 913 (2019).</li><li>Turner, K. H., Wessel, A. K., Palmer, G. C., Murray, J. L., Whiteley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Essential+genome+of+Pseudomonas+aeruginosa+in+cystic+fibrosis+sputum.">Essential genome of Pseudomonas aeruginosa in cystic fibrosis sputum.</a> Proceedings of the National Academy of Sciences of the United States of America. 112 (13), 4110-4115 (2015).</li><li>Darch, S. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phage+inhibit+pathogen+dissemination+by+targeting+bacterial+migrants+in+a+chronic+infection+model.">Phage inhibit pathogen dissemination by targeting bacterial migrants in a chronic infection model.</a> MBio. 8 (2), 00240 (2017).</li><li>Jorth, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regional+isolation+drives+bacterial+diversification+within+cystic+fibrosis+lungs.">Regional isolation drives bacterial diversification within cystic fibrosis lungs.</a> Cell Host &amp; Microbe. 18 (3), 307-319 (2015).</li><li>Palmer, K. L., Aye, L. M., Whiteley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nutritional+cues+control+Pseudomonas+aeruginosa+multicellular+behavior+in+cystic+fibrosis+sputum.">Nutritional cues control Pseudomonas aeruginosa multicellular behavior in cystic fibrosis sputum.</a> Journal of Bacteriology. 189 (22), 8079-8087 (2007).</li><li>Davies, D. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+involvement+of+cell-to-cell+signals+in+the+development+of+a+bacterial+biofilm.">The involvement of cell-to-cell signals in the development of a bacterial biofilm.</a> Science. 280 (5361), 295-298 (1998).</li><li>Hartmann, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+image+analysis+of+microbial+communities+with+BiofilmQ.">Quantitative image analysis of microbial communities with BiofilmQ.</a> Nature Microbiology. 6 (2), 151-156 (2021).</li><li>Stacy, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+fight-and-flight+responses+enhance+virulence+in+a+polymicrobial+infection.">Bacterial fight-and-flight responses enhance virulence in a polymicrobial infection.</a> Proceedings of the National Academy of Sciences of the United States of America. 111 (21), 7819-7824 (2014).</li></ol>

The authors have no conflicts of interest.

This work has introduced methodologies that can be combined to study bacterial aggregate populations in the presence and absence of antibiotic treatment. High-resolution CLSM allows the visualization of changes in aggregate biomass and the structural orientation of aggregates over real time when exposed to antibiotics. In addition, physical and structural features of the biomass that remain after treatment with antibiotics can be quantified, with the goal to correlate these observations with future gene expression studie...

Pseudomonas aeruginosa (Pa) is an opportunistic pathogen that establishes chronic infections in immune-compromised individuals. For those with the genetic disease cystic fibrosis&#160;(CF), these infections can span the course of a lifetime. CF causes the buildup of a viscous, nutrient-rich sputum in the airways, which becomes colonized by a variety of microbial pathogens over time. Pa is one of the most prevalent CF pathogens, colonizing the airways in early childhood and establishing difficult-to-treat infections1. Pa remains a significant clinical problem and is considered a leading cause of mortality in those with CF, despite improved therapy regimens in recent years2,3. This persistence phenotype and increasing antibiotic tolerance have earned Pa a place in a group of pathogens identified by both the Centers for Disease Control (CDC) and the World Health Organization (WHO) as research priorities for the development of new therapeutic strategies-the ESKAPE pathogens4.
Like other ESKAPE pathogens, acquired antibiotic resistance is common in Pa, but there are also many intrinsic properties that contribute to Pa antimicrobial tolerance. Among these is the ability of Pa to form aggregates-highly dense clusters of ~10-1,000 cells, which can be observed in multiple infections, including CF patient sputum5,6. Similar to Pa studied in other biofilm systems, Pa aggregates display clinically relevant phenotypes such as increased resistance to antibiotics and activation of cell-cell communication (quorum sensing (QS)). For example, aggregates of Pa have been shown to use QS-regulated behaviors to combat other microbes as well as tolerate antimicrobial treatments such as the production of pyocyanin7. The ability to study such behaviors offers an exciting insight into bacterial ecosystems in an environment similar to the one in which they exist in the human body.
One of the biggest challenges to studying how Pa aggregates respond to the changing sputum environment is the lack of nutritionally relevant and robust systems that promote aggregate formation. Much of what is known about Pa has been discovered using in vitro systems in which cells grow planktonically or in a characteristic surface-attached, &#34;mushroom&#34; architecture that has not been observed in vivo8. While classical biofilm growth models, such as flow cells or solid agar, have yielded extensive and valuable knowledge about bacterial behaviors and mechanisms of antibiotic tolerance, these findings do not always translate in vivo. Many in vitro models have a limited ability to mimic the growth environment of the human infection site, necessitating costly in vivo studies. In turn, many in vivo models lack the flexibility and resolution afforded by in vitro techniques.
Synthetic cystic fibrosis sputum (SCFM2) is designed to provide an environment for Pa growth similar to that experienced during chronic infection in the CF lung. SCFM2 includes nutritional sources identified in expectorated CF sputa in addition to mucin, lipids, and DNA. Pa growth in SCFM2 requires a near identical gene set to that required for growth in actual sputum and supports natural Pa aggregate formation9,10. After inoculation, planktonic cells form aggregates that increase in size through expansion. Individual cells (referred to as migrants) are released from aggregates, migrate to uncolonized areas, and form new aggregates10. This life history can be observed using CLSM and image analysis at the resolution of a single cell. Aggregates of Pa formed in SCFM2 are of similar sizes to those observed in the CF lung10. This model allows the observation of multiple aggregates of varying size in real-time and in three dimensions at the micron scale. Time-lapse microscopy allows the tracking of thousands (~50,000) of aggregates in one experiment. The use of image analysis software allows the quantification of aggregate phenotypes from micrographs, including aggregate volume, surface area, and position in three dimensions to the nearest 0.1 &#956;m, both at the individual aggregate and population levels. Having the ability to group aggregates by phenotype and position allows the differentiation of aggregates at different developmental stages with precision, as well as their response to a changing microenvironment6,11.
The application of SCFM2 to study Pa aggregates in low volume and high-throughput assays make it a flexible, cost-effective model. As a defined medium, SCFM2 offers uniformity and reproducibility across multiple platforms, providing a nutritionally and physically relevant method to study Pa aggregates in vitro9. Applications include its use in combination with CLSM to observe spatial organization and antibiotic tolerance at high resolution (as described in this methods paper). The ability to perform experiments that provide real-time, micron-scale data allows the study of intra-species and inter-species interactions as they may occur in vivo. For example, SCFM2 has previously been used to study the spatial dynamics of cell-cell communication in aggregate populations via a network of systems utilized by Pa to regulate multiple genes that contribute to virulence and pathogenesis6.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/62420/62420fig01.jpg" /> 
Figure 1: Graphical depiction of the main experimental steps. (A) SCFM2 is inoculated with Pa cells and allowed to form&#160;aggregates in a glass-bottomed culture dish. (B) Aggregates are transferred to the confocal microscope, and antibiotic is added. Depicted are three technical replicates (chambers 1-3) and a control well (4) of inoculated SCFM2 without antibiotic treatment. Aggregates are imaged using CLSM over the course of 18 h. (C) After the initial 18-h imaging, aggregates are treated with propidium iodide to visualize dead cells and imaged using CLSM (D) Aggregates with desired phenotype are separated from SCFM2 using FACS. Abbreviations: SCFM2 = synthetic cystic fibrosis sputum medium; Pa = Pseudomonas aeruginosa; CLSM = confocal laser scanning microscopy; FACS = fluorescence-activated cell sorting. <a href="https://www.jove.com/files/ftp_upload/62420/62420fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Here, the utility of SCFM2 to study the impact of antibiotic treatment on Pa aggregates in real time is demonstrated, followed by the use of a cell-sorting approach to isolate populations of aggregates with distinct phenotypes for downstream analysis (Figure 1).

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Amino acids</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Alanine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>56-41-7</td>
			<td></td>
		</tr>
		<tr>
			<td>Arginine HCl</td>
			<td>MP</td>
			<td>1119-34-2</td>
			<td></td>
		</tr>
		<tr>
			<td>Asparagine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>56-84-8</td>
			<td>Prepared in 0.5 M NaOH</td>
		</tr>
		<tr>
			<td>Cystine HCl</td>
			<td>Alfa Aesar</td>
			<td>L06328</td>
			<td></td>
		</tr>
		<tr>
			<td>Glutamic acid HCl</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>138-15-8</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>56-40-6</td>
			<td></td>
		</tr>
		<tr>
			<td>Histidine HCl H2O</td>
			<td>Alfa Aesar</td>
			<td>A17627</td>
			<td></td>
		</tr>
		<tr>
			<td>Isoleucine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>73-32-5</td>
			<td></td>
		</tr>
		<tr>
			<td>Leucine</td>
			<td>Alfa Aesar</td>
			<td>A12311</td>
			<td></td>
		</tr>
		<tr>
			<td>Lysine HCl</td>
			<td>Alfa Aesar</td>
			<td>J62099</td>
			<td></td>
		</tr>
		<tr>
			<td>Methionine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>63-68-3</td>
			<td></td>
		</tr>
		<tr>
			<td>Ornithine HCl</td>
			<td>Alfa Aesar</td>
			<td>A12111</td>
			<td></td>
		</tr>
		<tr>
			<td>Phenylalanine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>63-91-2</td>
			<td></td>
		</tr>
		<tr>
			<td>Proline</td>
			<td>Alfa Aesar</td>
			<td>A10199</td>
			<td></td>
		</tr>
		<tr>
			<td>Serine</td>
			<td>Alfa Aesar</td>
			<td>A11179</td>
			<td></td>
		</tr>
		<tr>
			<td>Threonine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>72-19-5</td>
			<td></td>
		</tr>
		<tr>
			<td>Tryptophan</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>73-22-3</td>
			<td>Prepared in 0.2 M NaOH</td>
		</tr>
		<tr>
			<td>Tyrosine</td>
			<td>Alfa Aesar</td>
			<td>A11141</td>
			<td>Prepared in 1.0 M NaOH</td>
		</tr>
		<tr>
			<td>Valine</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>72-18-4</td>
			<td></td>
		</tr>
		<tr>
			<td>Antibiotic</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Carbenicillin</td>
			<td>Alfa Aesar</td>
			<td>J6194903</td>
			<td></td>
		</tr>
		<tr>
			<td>Day-of Stocks</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>CaCl2 * 2H2O</td>
			<td>Fisher Chemical</td>
			<td>C79-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Dextrose (D-glucose)</td>
			<td>Fisher Chemical</td>
			<td>50-99-7</td>
			<td></td>
		</tr>
		<tr>
			<td>1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)</td>
			<td>Fisher (Avanti Polar Lipids)</td>
			<td>4235-95-4</td>
			<td>shake 15-20 min at 37 &#176;C to evaporate chloroform</td>
		</tr>
		<tr>
			<td>FeSO4 * 7H2O</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>7782-63-0</td>
			<td>this stock equals 1 mg/mL, MUST make fresh</td>
		</tr>
		<tr>
			<td>L-lactic acid</td>
			<td>Alfa Aesar</td>
			<td>L13242</td>
			<td>pH stock to 7 with NaOH</td>
		</tr>
		<tr>
			<td>MgCl2 * 6H2O</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>7791-18-6</td>
			<td></td>
		</tr>
		<tr>
			<td>N-acetylglucosamine</td>
			<td>&#160;TCI</td>
			<td>A0092</td>
			<td></td>
		</tr>
		<tr>
			<td>Prepared solids</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Porcine mucin</td>
			<td>Sigma</td>
			<td>M1778-100G</td>
			<td>UV-sterilize</td>
		</tr>
		<tr>
			<td>Salmon sperm DNA</td>
			<td>Invitrogen</td>
			<td>15632-011</td>
			<td></td>
		</tr>
		<tr>
			<td>Stain</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Propidium iodide</td>
			<td>Alfa Aesar</td>
			<td>J66764MC</td>
			<td></td>
		</tr>
		<tr>
			<td>Salts</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>K2SO4</td>
			<td>Alfa Aesar</td>
			<td>A13975</td>
			<td></td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>Alfa Aesar</td>
			<td>J64189</td>
			<td>add solid directly to buffered base</td>
		</tr>
		<tr>
			<td>KNO3</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>7757-79-1</td>
			<td></td>
		</tr>
		<tr>
			<td>MOPS</td>
			<td>Alfa Aesar</td>
			<td>A12914</td>
			<td>add solid directly to buffered base</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>Fisher Chemical</td>
			<td>S271-500</td>
			<td>add solid directly to buffered base</td>
		</tr>
		<tr>
			<td>Na2HPO4</td>
			<td>RPI</td>
			<td>S23100-500.0</td>
			<td></td>
		</tr>
		<tr>
			<td>NaH2PO4</td>
			<td>RPI</td>
			<td>S23120-500.0</td>
			<td></td>
		</tr>
		<tr>
			<td>NH4Cl</td>
			<td>Acr<img alt="Equation 1" src="/files/ftp_upload/62420/62420eq1v10.png" />s Organics</td>
			<td>12125-02-9</td>
			<td>add solid directly to buffered base</td>
		</tr>
		<tr>
			<td>Consumables</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Conical tubes (15 mL)</td>
			<td>Olympus plastics</td>
			<td>28-101</td>
			<td></td>
		</tr>
		<tr>
			<td>Conical tubes (50 mL)</td>
			<td>Olympus plastics</td>
			<td>28-106</td>
			<td></td>
		</tr>
		<tr>
			<td>Culture tubes w/air flow cap</td>
			<td>Olympus plastics</td>
			<td>21-129</td>
			<td></td>
		</tr>
		<tr>
			<td>35 mm four chamber glass-bottom dish</td>
			<td>CellVis</td>
			<td>NC0600518</td>
			<td></td>
		</tr>
		<tr>
			<td>Luria Bertani (LB) broth</td>
			<td>Genessee Scientific</td>
			<td>11-118</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate-buffered saline (PBS)</td>
			<td>Fisher Bioreagents</td>
			<td>BP2944100</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips (p200)</td>
			<td>Olympus plastics</td>
			<td>23-150RL</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips (p1000)</td>
			<td>Olympus plastics</td>
			<td>23-165RL</td>
			<td></td>
		</tr>
		<tr>
			<td>Serological pipets (5 mL)</td>
			<td>Olympus plastics</td>
			<td>12-102</td>
			<td></td>
		</tr>
		<tr>
			<td>Serological pipets (25 mL)</td>
			<td>Olympus plastics</td>
			<td>12-106</td>
			<td></td>
		</tr>
		<tr>
			<td>Serological pipets (50 mL)</td>
			<td>Olympus plastics</td>
			<td>12-107</td>
			<td></td>
		</tr>
		<tr>
			<td>Ultrapure water (RNAse/DNAse free); nanopure water</td>
			<td>Genessee Scientific</td>
			<td>18-194</td>
			<td>Nanopure water used for preparation of solutions in Table 1</td>
		</tr>
		<tr>
			<td>Syringes (10&#160; mL)</td>
			<td>BD</td>
			<td>794412</td>
			<td></td>
		</tr>
		<tr>
			<td>Syringes (50 mL)</td>
			<td>BD</td>
			<td>309653</td>
			<td></td>
		</tr>
		<tr>
			<td>0.22 mm PES syringe filter</td>
			<td>Olympus plastics</td>
			<td>25-244</td>
			<td></td>
		</tr>
		<tr>
			<td>PS cuvette semi-mico</td>
			<td>Olympus plastics</td>
			<td>91-408</td>
			<td></td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Biorender</td>
			<td></td>
			<td></td>
			<td>To prepare the figures</td>
		</tr>
		<tr>
			<td>FacsDiva6.1.3</td>
			<td>Becton Dickinson, San Jose, CA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Imaris</td>
			<td>Bitplane</td>
			<td></td>
			<td>version 9.6</td>
		</tr>
		<tr>
			<td>Zen Black</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>FacsAriallu</td>
			<td>Becton Dickinson, San Jose, CA</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>LSM 880 confocal laser scanning microscope</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

tools for the real-time assessment of a pseudomonas aeruginosa infection model

Pseudomonas aeruginosa (Pa) is one of the most common opportunistic pathogens associated with cystic fibrosis (CF). Once Pa colonization is established, a large proportion of the infecting bacteria form biofilms within airway sputum. Pa biofilms isolated from CF sputum have been shown to grow in small, dense aggregates of ~10-1,000 cells that are spatially organized and exhibit clinically relevant phenotypes such as antimicrobial tolerance. One of the biggest challenges to studying how Pa aggregates respond to the changing sputum environment is the lack of nutritionally relevant and robust systems that promote aggregate formation. Using a synthetic CF sputum medium (SCFM2), the life history of Pa aggregates can be observed using confocal laser scanning microscopy (CLSM) and image analysis at the resolution of a single cell. This in vitro system allows the observation of thousands of aggregates of varying size in real time, three dimensions, and at the micron scale. At the individual and population levels, having the ability to group aggregates by phenotype and position facilitates the observation of aggregates at different developmental stages and their response to changes in the microenvironment, such as antibiotic treatment, to be differentiated with precision.

This work details methods to observe Pa aggregates at a high resolution and in an environment similar to that of chronic infection of the CF lung9,10,12. SCFM2 provides an in vitro system that promotes natural aggregation of Pa cells in sizes similar to those observed during actual infection10. The adaptability of SCFM2 as a defined medium can be leveraged to approach many resea...

Watch this Scientific Journal Video about Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model at JoVE.com

Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model

Synthetic cystic fibrosis sputum medium (SCFM2) can be utilized in combination with both confocal laser scanning microscopy and fluorescence-activated cell sorting to observe bacterial aggregates at high resolution. This paper details methods to assess aggregate populations during antimicrobial treatment as a platform for future studies.

Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model

Pseudomonas aeruginosa (Pa) is one of the most common opportunistic pathogens associated with cystic fibrosis (CF). Once Pa colonization is established, a ...

tools-for-real-time-assessment-pseudomonas-aeruginosa-infection

Research

JoVE Journal

Immunology and Infection

3.3K Views.  Morsani College of Medicine, University of South Florida. Synthetic cystic fibrosis sputum medium (SCFM2) can be utilized in combination with both confocal laser scanning microscopy and fluorescence-activated cell sorting to observe bacterial aggregates at high resolution. This paper details methods to assess aggregate populations during antimicrobial treatment as a platform for future studies. 

Video: Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model

Co-culture Models of Pseudomonas aeruginosa Biofilms Grown on Live Human Airway Cells

Bacterial biofilms have been associated with a number of different human diseases, but biofilm development has generally been studied on non-living surfaces. In this paper, we describe protocols for forming Pseudomonas aeruginosa biofilms on human airway epithelial cells (CFBE cells) grown in culture. In the first method (termed the Static Co-culture Biofilm Model), P. aeruginosa is incubated with CFBE cells grown as confluent monolayers on standard tissue culture plates. Although the bacterium is quite toxic to epithelial cells, the addition of arginine delays the destruction of the monolayer long enough for biofilms to form on the CFBE cells. The second method (termed the Flow Cell Co-culture Biofilm Model), involves adaptation of a biofilm flow cell apparatus, which is often used in biofilm research, to accommodate a glass coverslip supporting a confluent monolayer of CFBE cells. This monolayer is inoculated with P. aeruginosa and a peristaltic pump then flows fresh medium across the cells. In both systems, bacterial biofilms form within 6-8 hours after inoculation. Visualization of the biofilm is enhanced by the use of P. aeruginosa strains constitutively expressing green fluorescent protein (GFP). The Static and Flow Cell Co-culture Biofilm assays are model systems for early P. aeruginosa infection of the Cystic Fibrosis (CF) lung, and these techniques allow different aspects of P. aeruginosa biofilm formation and virulence to be studied, including biofilm cytotoxicity, measurement of biofilm CFU, and staining and visualizing the biofilm.

Co-culture Models of Pseudomonas aeruginosa Biofilms Grown on Live Human Airway Cells

This paper describes different methods of growing Pseudomonas aeruginosa biofilms on cultured human airway epithelial cells. These protocols can be adapted to study different aspects of biofilm formation, including visualization of the biofilm, staining of the biofilm, measuring the colony forming units (CFU) of the biofilm, and studying biofilm cytotoxicity.

Bacterial biofilms have been associated with a number of different human diseases, but biofilm development has generally been studied on non-living ...

Pseudomonas aeruginosa and Saccharomyces cerevisiae Biofilm in Flow Cells

Many microbial cells have the ability to form sessile microbial communities defined as biofilms that have altered physiological and pathological properties compared to free living microorganisms. Biofilms in nature are often difficult to investigate and reside under poorly defined conditions1. Using a transparent substratum it is possible to device a system where simple biofilms can be examined in a non-destructive way in real-time: here we demonstrate the assembly and operation of a flow cell model system, for in vitro 3D studies of microbial biofilms generating high reproducibility under well-defined conditions2,3.
The system consists of a flow cell that serves as growth chamber for the biofilm. The flow cell is supplied with nutrients and oxygen from a medium flask via a peristaltic pump and spent medium is collected in a waste container. This construction of the flow system allows a continuous supply of nutrients and administration of e.g. antibiotics with minimal disturbance of the cells grown in the flow chamber. Moreover, the flow conditions within the flow cell allow studies of biofilm exposed to shear stress. A bubble trapping device confines air bubbles from the tubing which otherwise could disrupt the biofilm structure in the flow cell.
The flow cell system is compatible with Confocal Laser Scanning Microscopy (CLSM) and can thereby provide highly detailed 3D information about developing microbial biofilms. Cells in the biofilm can be labeled with fluorescent probes or proteins compatible with CLSM analysis. This enables online visualization and allows investigation of niches in the developing biofilm. Microbial interrelationship, investigation of antimicrobial agents or the expression of specific genes, are of the many experimental setups that can be investigated in the flow cell system.

Pseudomonas aeruginosa and Saccharomyces cerevisiae Biofilm in Flow Cells

Protocol describing the application of a flow cell system for growing and analyzing microbial biofilms for Confocal Laser Scanning Microscopy (CLSM).

Many microbial cells have the ability to form sessile microbial communities defined as biofilms that have altered physiological and pathological ...

RNA Isolation of Pseudomonas aeruginosa Colonizing the Murine Gastrointestinal Tract

Pseudomonas aeruginosa (PA) infections result in significant morbidity and mortality in hosts with compromised immune systems, such as patients with leukemia, severe burn wounds, or organ transplants1. In patients at high-risk for developing PA bloodstream infections, the gastrointestinal (GI) tract is the main reservoir for colonization2, but the mechanisms by which PA transitions from an asymptomatic colonizing microbe to an invasive, and often deadly, pathogen are unclear. Previously, we performed in vivo transcription profiling experiments by recovering PA mRNA from bacterial cells residing in the cecums of colonized mice 3 in order to identify changes in bacterial gene expression during alterations to the host&#x2019;s immune status.
As with any transcription profiling experiment, the rate-limiting step is in the isolation of sufficient amounts of high quality mRNA. Given the abundance of enzymes, debris, food residues, and particulate matter in the GI tract, the challenge of RNA isolation is daunting. Here, we present a method for reliable and reproducible isolation of bacterial RNA recovered from the murine GI tract. This method utilizes a well-established murine model of PA GI colonization and neutropenia-induced dissemination4. Once GI colonization with PA is confirmed, mice are euthanized and cecal contents are recovered and flash frozen. RNA is then extracted using a combination of mechanical disruption, boiling, phenol/chloroform extractions, DNase treatment, and affinity chromatography. Quantity and purity are confirmed by spectrophotometry (Nanodrop Technologies) and bioanalyzer (Agilent Technologies) (Fig 1). This method of GI microbial RNA isolation can easily be adapted to other bacteria and fungi as well.

RNA Isolation of Pseudomonas aeruginosa Colonizing the Murine Gastrointestinal Tract

A reliable method for the RNA isolation of Pseudomonas aeruginosa recovered from murine cecums is described. The RNA recovered is of sufficient quantity and quality for subsequent qPCR, transcription profiling, and RNA Seq experiments. This technique can be adapted for RNA isolation of other intestinal microbes.

Pseudomonas aeruginosa (PA) infections result in significant morbidity and mortality in hosts with compromised immune systems, such as patients with ...

Use of Artificial Sputum Medium to Test Antibiotic Efficacy Against Pseudomonas aeruginosa in Conditions More Relevant to the Cystic Fibrosis Lung

There is growing concern about the relevance of in vitro antimicrobial susceptibility tests when applied to isolates of P. aeruginosa from cystic fibrosis (CF) patients. Existing methods rely on single or a few isolates grown aerobically and planktonically. Predetermined cut-offs are used to define whether the bacteria are sensitive or resistant to any given antibiotic1. However, during chronic lung infections in CF, P. aeruginosa populations exist in biofilms and there is evidence that the environment is largely microaerophilic2. The stark difference in conditions between bacteria in the lung and those during diagnostic testing has called into question the reliability and even relevance of these tests3.
 Artificial sputum medium (ASM) is a culture medium containing the components of CF patient sputum, including amino acids, mucin and free DNA. P. aeruginosa growth in ASM mimics growth during CF infections, with the formation of self-aggregating biofilm structures and population divergence4,5,6. The aim of this study was to develop a microtitre-plate assay to study antimicrobial susceptibility of P. aeruginosa based on growth in ASM, which is applicable to both microaerophilic and aerobic conditions.
 An ASM assay was developed in a microtitre plate format. P. aeruginosa biofilms were allowed to develop for 3 days prior to incubation with antimicrobial agents at different concentrations for 24 hours. After biofilm disruption, cell viability was measured by staining with resazurin. This assay was used to ascertain the sessile cell minimum inhibitory concentration (SMIC) of tobramycin for 15 different P. aeruginosa isolates under aerobic and microaerophilic conditions and SMIC values were compared to those obtained with standard broth growth. Whilst there was some evidence for increased MIC values for isolates grown in ASM when compared to their planktonic counterparts, the biggest differences were found with bacteria tested in microaerophilic conditions, which showed a much increased resistance up to a &gt;128 fold, towards tobramycin in the ASM system when compared to assays carried out in aerobic conditions.
 The lack of association between current susceptibility testing methods and clinical outcome has questioned the validity of current methods3. Several in vitro models have been used previously to study P. aeruginosa biofilms7, 8. However, these methods rely on surface attached biofilms, whereas the ASM biofilms resemble those observed in the CF lung9 . In addition, reduced oxygen concentration in the mucus has been shown to alter the behavior of P. aeruginosa2 and affect antibiotic susceptibility10. Therefore using ASM under microaerophilic conditions may provide a more realistic environment in which to study antimicrobial susceptibility.

Use of Artificial Sputum Medium to Test Antibiotic Efficacy Against Pseudomonas aeruginosa in Conditions More Relevant to the Cystic Fibrosis Lung

Current diagnostic antimicrobial susceptibility testing relies on the planktonic growth of isolates in nutrient rich, aerobic conditions. Here, we employ an alternative artificial sputum medium to study antimicrobial susceptibility of Pseudomonas aeruginosa biofilms under both aerobic and microaerophilic conditions more representative of the cystic fibrosis lung.

There  is growing concern about the relevance of in vitro antimicrobial  susceptibility tests when applied to isolates of P. aeruginosa from  cystic ...

Long Term Chronic Pseudomonas aeruginosa Airway Infection in Mice

A mouse model of chronic airway infection is a key asset in cystic fibrosis (CF) research, although there are a number of concerns regarding the model itself. Early phases of inflammation and infection have been widely studied by using the Pseudomonas aeruginosa agar-beads mouse model, while only few reports have focused on the long-term chronic infection in vivo. The main challenge for long term chronic infection remains the low bacterial burden by P. aeruginosa and the low percentage of infected mice weeks after challenge, indicating that bacterial cells are progressively cleared by the host.
This paper presents a method for obtaining efficient long-term chronic infection in mice. This method is based on the embedding of the P. aeruginosa clinical strains in the agar-beads in vitro, followed by intratracheal instillation in C57Bl/6NCrl mice. Bilateral lung infection is associated with several measurable read-outs including weight loss, mortality, chronic infection, and inflammatory response. The P. aeruginosa RP73 clinical strain was preferred over the PAO1 reference laboratory strain since it resulted in a comparatively lower mortality, more severe lesions, and higher chronic infection. P. aeruginosa colonization may persist in the lung for over three months. Murine lung pathology resembles that of CF patients with advanced chronic pulmonary disease.
This murine model most closely mimics the course of the human disease and can be used both for studies on the pathogenesis and for the evaluation of novel therapies.

Long Term Chronic Pseudomonas aeruginosa Airway Infection in Mice

We describe the agar-beads method to establish persistent long-term chronic Pseudomonas aeruginosa airway infection in the mouse model.

A mouse model of chronic airway infection is a key asset in cystic fibrosis (CF) research, although there are a number of concerns regarding the model ...

Pseudomonas aeruginosa Induced Lung Injury Model

In order to study human acute lung injury and pneumonia, it is important to develop animal models to mimic various pathological features of this disease. Here we have developed a mouse lung injury model by intra-tracheal injection of bacteria Pseudomonas aeruginosa (P. aeruginosa or PA). Using this model, we were able to show lung inflammation at the early phase of injury. In addition, alveolar epithelial barrier leakiness was observed by analyzing bronchoalveolar lavage (BAL); and alveolar cell death was observed by Tunel assay using tissue prepared from injured lungs. At a later phase following injury, we observed cell proliferation required for the repair process. The injury was resolved 7 days from the initiation of P. aeruginosa injection. This model mimics the sequential course of lung inflammation, injury and repair during pneumonia. This clinically relevant animal model is suitable for studying pathology, mechanism of repair, following acute lung injury, and also can be used to test potential therapeutic agents for this disease.

Pseudomonas aeruginosa Induced Lung Injury Model

We have developed a mouse lung injury model by intra-tracheal injection of bacteria Pseudomonas aeruginosa. This model mimics lung injury during pneumonia and is clinically relevant.

In order to study human acute lung injury and pneumonia, it is important to develop animal models to mimic various pathological features of this disease. ...

Studying Microbial Communities In Vivo: A Model of Host-mediated Interaction Between Candida Albicans and Pseudomonas Aeruginosa in the Airways

Studying host-pathogen interaction enables us to understand the underlying mechanisms of the pathogenicity during microbial infection. The prognosis of the host depends on the involvement of an adapted immune response against the pathogen1. Immune response is complex and results from interaction of the pathogens and several immune or non-immune cellular types2. In vitro studies cannot characterise these interactions and focus on cell-pathogen interactions. Moreover, in the airway3, particularly in patients with suppurative chronic lung disease or in mechanically ventilated patients, polymicrobial communities are present and complicate host-pathogen interaction. Pseudomonas aeruginosa and Candida albicans are both problem pathogens4, frequently isolated from tracheobronchial samples, and associated to severe infections, especially in intensive care unit5. Microbial interactions have been reported between these pathogens in vitro but the clinical impact of these interactions remains unclear6. To study the interactions between C. albicans and P. aeruginosa, a murine model of C. albicans airways colonization, followed by a P. aeruginosa-mediated acute lung infection was performed.

Studying Microbial Communities In Vivo: A Model of Host-mediated Interaction Between Candida Albicans and Pseudomonas Aeruginosa in the Airways

While in vitro study of host-pathogen interactions allow the characterization of specific immune responses, in vivo models are required to observe the effects of complex responses. Using Candida albicans exposure followed by Pseudomonas aeruginosa-mediated lung infection, we established a murine model of microbial interactions involved in ventilator-associated pneumonia pathogenicity.

Studying host-pathogen interaction enables us to understand the underlying mechanisms of the pathogenicity during microbial infection. The prognosis of ...

Come to the Light Side: In Vivo Monitoring of Pseudomonas aeruginosa Biofilm Infections in Chronic Wounds in a Diabetic Hairless Murine Model

The presence of bacteria as structured biofilms in chronic wounds, especially in diabetic patients, is thought to prevent wound healing and resolution. Chronic mouse wounds models have been used to understand the underlying interactions between the microorganisms and the host. The models developed to date rely on the use of haired animals and terminal collection of wound tissue for determination of viable bacteria. While significant insight has been gained with these models, this experimental procedure requires a large number of animals and sampling is time consuming. We have developed a novel murine model that incorporates several optimal innovations to evaluate biofilm progression in chronic wounds: a) it utilizes hairless mice, eliminating the need for hair removal; b) applies pre-formed biofilms to the wounds allowing for the immediate evaluation of persistence and effect of these communities on host; c) monitors biofilm progression by quantifying light production by a genetically engineered bioluminescent strain of Pseudomonas aeruginosa, allowing real-time monitoring of the infection thus reducing the number of animals required per study. In this model, a single full-depth wound is produced on the back of STZ-induced diabetic hairless mice and inoculated with biofilms of the P. aeruginosa bioluminescent strain Xen 41. Light output from the wounds is recorded daily in an in vivo imaging system, allowing for in vivo and in situ rapid biofilm visualization and localization of biofilm bacteria within the wounds. This novel method is flexible as it can be used to study other microorganisms, including genetically engineered species and multi-species biofilms, and may be of special value in testing anti-biofilm strategies including antimicrobial occlusive dressings.

Come to the Light Side: In Vivo Monitoring of Pseudomonas aeruginosa Biofilm Infections in Chronic Wounds in a Diabetic Hairless Murine Model

Here we describe a novel diabetic murine model utilizing hairless mice for real-time, non-invasive, monitoring of biofilm wound infections of bioluminescent Pseudomonas aeruginosa. This method can be adapted to evaluate infection of other bacterial species and genetically modified microorganisms, including multi-species biofilms, and test the efficacy of antibiofilm strategies.

The presence of bacteria as structured biofilms in chronic wounds, especially in diabetic patients, is thought to prevent wound healing and resolution. ...

Replication of the Ordered, Nonredundant Library of Pseudomonas aeruginosa strain PA14 Transposon Insertion Mutants

Pseudomonas aeruginosa is a phenotypically and genotypically diverse and adaptable Gram-negative bacterium ubiquitous in human environments. P. aeruginosa is able to form biofilms, develop antibiotic resistance, produce virulence factors, and rapidly evolve in the course of a chronic infection. Thus P. aeruginosa can cause both acute and chronic, difficult to treat infections, resulting in significant morbidity in certain patient populations. P. aeruginosa strain PA14 is a human clinical isolate with a conserved genome structure that infects a variety of mammalian and nonvertebrate hosts making PA14 an attractive strain for studying this pathogen. In 2006, a nonredundant transposon insertion mutant library containing 5,459 mutants corresponding to 4,596 predicted PA14 genes was generated. Since then, distribution of the PA14 library has allowed the research community to better understand the function of individual genes and complex pathways of P. aeruginosa. Maintenance of library integrity through the replication process requires proper handling and precise techniques. To that end, this manuscript presents protocols that describe in detail the steps involved in library replication, library quality control and proper storage of individual mutants.

Replication of the Ordered, Nonredundant Library of Pseudomonas aeruginosa strain PA14 Transposon Insertion Mutants

Pseudomonas aeruginosa infection causes significant morbidity in vulnerable hosts. The nonredundant transposon insertion mutant library of P. aeruginosa strain PA14, designated as PA14NR Set, facilitates analysis of gene functionality in numerous processes. Presented here is a protocol to generate high-quality copies of the PA14NR Set mutant library.

Pseudomonas aeruginosa is a phenotypically and genotypically diverse and adaptable Gram-negative bacterium ubiquitous in human environments. P. aeruginosa ...

Methods for Detecting Cytotoxic Amyloids Following Infection of Pulmonary Endothelial Cells by Pseudomonas aeruginosa

Patients who survive pneumonia have elevated death rates in the months following hospital discharge. It has been hypothesized that infection of pulmonary tissue during pneumonia results in the production of long-lived cytotoxins that can lead to subsequent end organ failure. We have developed in vitro assays to test the hypothesis that cytotoxins are produced during pulmonary infection. Isolated rat pulmonary endothelial cells and the bacterium Pseudomonas aeruginosa are used as model systems, and the production of cytoxins following infection of the endothelial cells by the bacteria is demonstrated using cell culture followed by direct quantitation using lactate dehydrogenase assays and a novel microscopic method utilizing ImageJ technology. The amyloid nature of these cytotoxins was demonstrated by thioflavin T binding assays and by immunoblotting and immunodepletion using A11 anti-amyloid antibody. Further analyses using immunoblotting demonstrated that oligomeric tau and A&#946; were produced and released by endothelial cells following infection by P. aeruginosa. These methods should be readily adaptable to analyses of human clinical samples.

Methods for Detecting Cytotoxic Amyloids Following Infection of Pulmonary Endothelial Cells by Pseudomonas aeruginosa

Simple methods are described for demonstrating the production of cytotoxic amyloids following infection of pulmonary endothelium by Pseudomonas aeruginosa.

Patients who survive pneumonia have elevated death rates in the months following hospital discharge. It has been hypothesized that infection of pulmonary ...

Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model

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Replication of the Ordered, Nonredundant Library of Pseudomonas aeruginosa strain PA14 Transposon Insertion Mutants

Methods for Detecting Cytotoxic Amyloids Following Infection of Pulmonary Endothelial Cells by Pseudomonas aeruginosa